Search Results for "g-code" - Page 52
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Showing 2698 open source projects for "g-code"
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Twinify
Privacy-preserving generation of a synthetic twin to a data set
twinify is a software package for the privacy-preserving generation of a synthetic twin to a given sensitive tabular data set. On a high level, twinify follows the differentially private data-sharing process introduced by Jälkö et al.. Depending on the nature of your data, twinify implements either the NAPSU-MQ approach described by Räisä et al. or finds an approximate parameter posterior for any probabilistic model you formulated using differentially private variational inference (DPVI).... -
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CleanRL
High-quality single file implementation of Deep Reinforcement Learning
...The implementation is clean and simple, yet we can scale it to run thousands of experiments using AWS Batch. CleanRL is not a modular library and therefore it is not meant to be imported. At the cost of duplicate code, we make all implementation details of a DRL algorithm variant easy to understand, so CleanRL comes with its own pros and cons. You should consider using CleanRL if you want to 1) understand all implementation details of an algorithm's variant or 2) prototype advanced features that other modular DRL libraries do not support (CleanRL has minimal lines of code so it gives you great debugging experience and you don't have to do a lot of subclassing like sometimes in modular DRL libraries). -
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Dummy-Robot
My super mini robotic arm robot project
Dummy-Robot is an open source robotics project by Peng Zhihui that showcases the design and implementation of a compact robotic arm . The repository contains full hardware design files, firmware, control software, and 3D models. It includes components such as a gripper, LED light ring PCB, wireless spatial positioning controller, and a portable case. The project demonstrates advanced engineering with stepper motor drivers, custom controllers, and debugging tools. While the original version... -
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Minimal text diffusion
A minimal implementation of diffusion models for text generation
A minimal implementation of diffusion models of text: learns a diffusion model of a given text corpus, allowing to generate text samples from the learned model. The main idea was to retain just enough code to allow training a simple diffusion model and generating samples, remove image-related terms, and make it easier to use. To train a model, run scripts/train.sh. By default, this will train a model on the simple corpus. However, you can change this to any text file using the --train_data argument. Note that you may have to increase the sequence length (--seq_len) if your corpus is longer than the simple corpus. ... -
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EnCodec
State-of-the-art deep learning based audio codec
...Encodec has applications in speech and music compression, generative modeling, and efficient data transmission for communication systems. The repository includes pretrained checkpoints, PyTorch inference code, and examples for integrating Encodec as a module in downstream generative or streaming systems. -
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G-CPS
Lite CPS Tester
G-CPS (Golden CPS) It is a Very Lite program to measure your CPS G-CPS is a very lightweight program, it contains multiple color themes, and several options to adjust the test time (1, 3, 5, 10, 15, 30 and 60) s. It also saves the CPS record that you have achieved, each time mode has a different record. Source Code: GitHub: https://github.com/PETEROLO291/G-CPS You can try it out with: https://sourceforge.net/projects/flame-auto-clicker/ Info: Installer: 9.3MB Program: 27.5MB Version: 2.1.1 - I am totally open to feature requests for future updates -
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FormaVid
Small Business Appliance
...The appliance is built using scripts so no hidden "monkey business" and you can choose a "compatible base distro" based on your needs: familiarity; performance; security; usability; etc. Please see https://sourceforge.net/p/formavid/code/ci/master/tree/INSTALL.txt for details. The appliance is specially designed to run on the Google Cloud Platform "Free Tier" https://formavid.org/gce and has it's own custom install script https://sourceforge.net/projects/formavid/files/gcloud-gce-deployment/download with instructions https://sourceforge.net/projects/formavid/files/ provided. -
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DialoGPT
Large-scale pretraining for dialogue
...The model was trained on a massive dataset of approximately 147 million conversational exchanges extracted from Reddit discussion threads, allowing it to learn patterns of natural human conversation. DialoGPT provides multiple pretrained model sizes and includes code for training, fine-tuning, and evaluating dialogue generation models. The repository also contains scripts for preparing conversation datasets and reproducing experimental benchmarks related to conversational AI research. -
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agglo
Multi facets CASE/AGL for easy project developments
Agglo is a CASE (Computer Aided Software Engineering) or AGL (Atelier Génie Logiciel), whose aim is to facilitate installation ans use of various tools (either existing opensource tools, or agglo tools), in several facets of project development: - requirements management - unit tests - automated integration tests - toolkit for various languages (cpp, c, python, shell, xsl) other facets are to come ultimately: - coverage tests - planification - integration with hudson - code quality analysis - indicator production -
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OpenOffice.org Utility Library
Library modules for creating ODF documents.
...These documents include many features including: - Create multiple table spreadsheets - Cells with text, numbers, dates, formulas - Ability to use built-in styles - Ability to create automatic styles (ie. bold, italics, underline, font size, font color, background color, etc.) - Set column and row attributes including width and height I am currently hosting the new development code at the following URL: https://github.com/josephcolton/ooolib-python I will be posting releases here on SourceForge as well as GitHub, so you can come to either place for the releases. The newest code will only be available using Git on GitHub. -
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CommandlineConfig
A library for users to write configurations in Python
CommandlineConfig is a lightweight Python library designed to simplify managing configuration parameters for experiments and applications, especially in research workflows that require frequent tweaking of hyperparameters. It lets you define configuration in familiar Python dictionaries or JSON files and then access nested parameters via dot notation in code, improving readability and reducing boilerplate. One of its core strengths is the ability to override configuration values directly from the command line, making it convenient to run many experimental variants without editing files repeatedly. The library supports arbitrarily deep nested structures, type handling, enumerated value constraints, and even tuple types, which are common in ML experiment setups. ... -
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Mouse Keyboard Clicker Holder
Autoclicker and holder for keyboard keys and mouse buttons
Autoclicker and holder for mouse buttons and keyboard keys. A small program to autoclick or hold a keyboard key or a mouse button. Can be downloaded as .exe as well as the original .py file. The source code is written in Python with alongside PySide6 and Pynput. The program is distributed under the Unlicense ( https://unlicense.org/ ) -
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Moriarty Project
Web-based OSINT tool for investigating phone number information
...Moriarty Project focuses strictly on OSINT-style information gathering and does not provide tracking, hacking, or harmful capabilities against phone number owners. It is fully open source, allowing users to inspect the code and understand how the data collection mechanisms work. -
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HelenOS
A microkernel-based multiserver operating system written from scratch.
...HelenOS does not aim to be a clone of any existing operating system and trades compatibility with legacy APIs for cleaner design. Most of HelenOS components have been made to order specifically for HelenOS so that its essential parts can stay free of adaptation layers, glue code, franken-components and the maintenance burden incurred by them. -
15
Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
...The project collects popular approaches such as dynamic programming, Monte Carlo methods, temporal difference learning, Q-learning, SARSA, deep Q-networks, and policy gradient techniques, often demonstrated with Python and OpenAI Gym environments so users can experiment with agents learning in simulated tasks. For each algorithm category, the repository pairs conceptual descriptions with runnable code and often illustrated exercises that help solidify understanding by bridging theory with practice. It’s structured to serve learners progressing from basic tabular methods to function approximation and deep learning extensions, making it suitable for students, researchers, or practitioners exploring reinforcement learning fundamentals. -
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Hacker Scripts
Based on a true story
Hacker Scripts is a cheeky collection of small automation scripts and language ports collected under the tagline “Based on a true story.” The repository gathers playful utilities (originally shell and Ruby scripts) that automate short, real-world tasks — for example, sending a quick “late at work” text when SSH sessions are active, firing off an automated “I’m sick / working from home” email on certain mornings, or even talking to a networked coffee machine to start brewing at precisely the... -
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Opta
The next generation of Infrastructure-as-Code
Opta is an infrastructure-as-code framework. Rather than working with a low-level cloud configuration, Opta enables you to work with high-level constructs. Opta high-level constructs produce Terraform configuration files. This helps you avoid lock-in to Opta. You can write custom Terraform code or even take the Opta-generated Terraform and go your own way. Opta is a new kind of Infrastructure-as-Code (IaC) framework that lets engineers work with high-level constructs instead of getting lost in low-level cloud configuration. ... -
18
Teleread
An e-book reading protocol for Linux and Windows
...Supported OS: Windows 7 Windows 8 Windows 8.1 Windows 10 Windows 11 Any Linux where python3 is installed For help, select help in the main menu NOTE: to download, click files, then select the version. For some reason it isn't letting me set it to download the main file WARNING: Source code is OUTDATED. For up to date source, visit https://github.com/Enderbyte-Programs/Teleread. If you wish to write your own books, please read the technical documentation or see the example book in the github repo. -
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VSCode-LaTeX-Inkscape
A way to integrate LaTeX, VS Code, and Inkscape in macOS
A way to integrate LaTeX, VS Code, and Inkscape in macOS. I use LaTeX heavily for both academic work and professional work, and I think I'm quite proficient in terms of typing things out in LaTeX. But when I see the mind-blowing blog posts from Gilles Castel (RIP)-How I'm able to take notes in mathematics lectures using LaTeX and Vim and also How I draw figures for my mathematical lecture notes using Inkscape, I realize that I'm still far from fast, so I decided to adapt the whole setup from Linux-Vim to macOS-VS Code. -
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DecryptLogin
Python library providing APIs for automated website login workflows
...It focuses on implementing login mechanisms through HTTP requests, allowing developers to programmatically authenticate with supported services without manually replicating complex login flows. It includes modules that handle different authentication modes such as PC login, mobile login, and QR code login depending on what the target platform supports. DecryptLogin supports a wide variety of online services and platforms, including social media sites, developer platforms, cloud services, and other web portals. Developers can integrate these login routines into automation scripts, crawlers, or data collection tools that require authenticated sessions. ... -
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codecat
static code analysis, to find/track sinks and bugs
CodeCat is a open source tool to help you in static code analysis, to find/track sinks and bugs, this points follow regex rules... -
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Reinforcement Learning Methods
Simple Reinforcement learning tutorials
Reinforcement-Learning-with-TensorFlow is an educational repository that walks through key reinforcement learning algorithms implemented in TensorFlow. It provides clear code examples for foundational techniques like Q-learning, policy gradients, deep Q-networks, actor-critic methods, and value function approximation within familiar simulation environments. Each algorithm is structured with readable code, explanatory comments, and corresponding environment interaction loops so learners can easily trace how actions, rewards, and model updates connect. ... -
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ostRAT
OpenSourceTelegramRAT - Remote PC access via Telegram Bot.
ostRAT is free and open source. GPLv3 Сomputer remote control software. Works via telegram bot. A lot of functions, for example: - Screenshot: sends a screenshot - Off: turns off the computer - Url: opens entered link - Write: sends your text to the computer - Move: changes mouse location with x and y - and more! WARNING: Using the bot is recommended only on your device. Failure to comply with the recommendation may result in criminal liability. -
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Apple Neural Engine (ANE) Transformers
Reference implementation of the Transformer architecture optimized
ANE Transformers is a reference PyTorch implementation of Transformer components optimized for Apple Neural Engine on devices with A14 or newer and on Macs with M1 or newer chips. It demonstrates how to structure attention and related layers to achieve substantial speedups and lower peak memory compared to baseline implementations when deployed to ANE. The repository targets practitioners who want to keep familiar PyTorch modeling while preparing models for Core ML/ANE execution paths.... -
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PyTorch Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, etc.
TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms or readily apply existing algorithms. We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please first open an issue and discuss the feature with us.
